Fingerprint identification system, fingerprint identification method, and electronic equipment

ABSTRACT

In the fingerprint identification system according to the present disclosure, the fingerprint sensor collects multiple frames of fingerprint images sliding-inputted by a user, the judging unit determines whether, among the multiple frames of fingerprint images, there is a first overlap region between a current frame of fingerprint images and a previous frame of fingerprint images; if yes, the judging unit removes the first overlap region from the current frame of fingerprint images and superposes the previous frame of fingerprint images with the current frame of fingerprint images to form a superposed fingerprint image; the judging unit completes judgment of all the multiple frames of fingerprint images to obtain a template fingerprint image; the processing unit saves characteristic points of the complete template fingerprint image. The fingerprint sensor collects a to-be-identified fingerprint image pressing-inputted by the user, and the processing unit determines whether the characteristic points of the to-be-identified fingerprint image match with the characteristic points of the template fingerprint image. When establishing template fingerprint database, the fingerprint identification system collects the fingerprint sliding-inputted by the user and the to-be-identified fingerprint pressing-inputted by the user in the subsequent matching process. Therefore, the input and identification efficiency is much higher than that of existing methods. The present disclosure also provides a fingerprint identification method and an electric equipment.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority and benefits of Chinese PatentApplication No. 201410799636.7, filed with State Intellectual PropertyOffice, P. R. C. on Dec. 19, 2014, the entire content of which isincorporated herein by reference.

FIELD

Embodiments of the present disclosure generally relate to a fingerprintidentification technology, and, more particularly, to a fingerprintidentification system, a fingerprint identification method, and anelectronic equipment.

BACKGROUND

Currently, area fingerprint sensors are using a pressing-style inputmethod. When inputting, the finger presses on a fingerprint sensor, thefingerprint sensor can obtain fingerprint information of the pressedpart of the finger at once, and there is no need to move the finger.However, because the area of the fingerprint scanning module is limited,the fingerprint sensor detects a relatively small area of the fingerevery time the finger presses, and relatively complete fingerprintinformation can be obtained by inputting several times.

At the same time, due to the structural limitation, or for betterappearance, the fingerprint scanning module of the fingerprint sensormay become smaller and smaller. When collecting a fingerprint, thefingerprint sensors collect less and less information from eachpressing, and the finger needs to press on the fingerprint sensor forseveral times to ensure that the fingerprint sensor can collect enoughcharacteristic points for subsequent matching processes. Thus, thecollecting process for a fingerprint database is tedious and very timeconsuming.

SUMMARY

The present disclosure seeks to solve at least one of the technicalproblems in the related art to some extent. Therefore, the presentdisclosure provides a fingerprint identification system, a fingerprintidentification method, and an electric equipment.

The fingerprint identification system includes a fingerprint sensor, ajudging unit and a processing unit, and:

the fingerprint sensor collects multiple frames of fingerprint imagessliding-inputted by a user;

the judging unit determines whether, among the multiple frames offingerprint images, there is a first overlap region between a currentframe of fingerprint images and a previous frame of fingerprint images;

when there is a first overlap region between a current frame offingerprint images and a previous frame of fingerprint images, thejudging unit removes the first overlap region from the current frame offingerprint images and superposes the previous frame of fingerprintimages with the current frame of fingerprint images without the firstoverlap region thereof to form a superposed fingerprint image; or thejudging unit removes the first overlap region from the previous frame offingerprint images and superposes the current frame of fingerprintimages with the previous frame of fingerprint images without the firstoverlap region to form the superposed fingerprint image;

the judging unit also judges whether there is a second overlap regionbetween a next frame of fingerprint images and the superposedfingerprint image, until completing judgment of all the multiple framesof fingerprint images to obtain a template fingerprint image;

when there is not a first overlap region between a current frame offingerprint images and a previous frame of fingerprint images, thefingerprint sensor collects new multiple frames of fingerprint imagessliding-inputted by the user;

the processing unit extracts and saves characteristic points of thecomplete template fingerprint image;

the fingerprint sensor collects a to-be-identified fingerprint imagepressing-inputted by the user, and the processing unit extractscharacteristic points of the to-be-identified fingerprint image anddetermines whether the characteristic points of the to-be-identifiedfingerprint image match with the characteristic points of the templatefingerprint image;

when the characteristic points of the to-be-identified fingerprint imagematch with the characteristic points of the template fingerprint image,the processing unit determines the to-be-identified fingerprint image asa matching fingerprint image; and

when the characteristic points of the to-be-identified fingerprint imagedo not match with the characteristic points of the template fingerprintimage, the processing unit determines the to-be-identified fingerprintimage as a non-matching fingerprint image.

According to the fingerprint identification system, when establishingthe template fingerprint database, the fingerprint sensor can be used tocollect the multiple frames of fingerprint images sliding-inputted bythe user, and the judging unit superposes the sliding-inputted framestogether using an image-stitching technique. Thus, the amount ofinformation collected by the fingerprint sensor for each sliding-inputis much more than the amount of information collected by the fingerprintsensor for each pressing-input under existing methods, and the inputefficiency is much higher than that of existing methods. The inputtingprocess can be completed by one-time collection of the left side, middleside, and right side of the finger, respectively, and is convenient toinput, avoiding complex operations and improving user experience. In thesubsequent matching process, the user presses the finger on thefingerprint sensor, and the fingerprint sensor can collect thefingerprint of the pressed-part of the finger, and the processing unitcan compare the collected fingerprint with template fingerprintdatabase. It is possible that the user uses regular angles wheninputting the fingerprints, but the matching process can still besuccessful at various angles.

In one embodiment, the processing unit is configured to performfiltering, binarization, and thinning processing on the templatefingerprint image, and to extract the characteristic points of thetemplate fingerprint image.

In one embodiment, the previous frame of fingerprint images includes theprevious frame image part, the current frame of fingerprint imagesincludes a plurality of current frame image parts, and the judging unitrespectively calculates gray differences between the first gray scale ofthe previous frame image part and corresponding second gray scales ofthe plurality of the current frame image parts to obtain a plurality ofthe gray scale differences, and to compare the plurality of the grayscale differences; and

when a gray scale difference between a second gray scale and the firstgray scale is a minimum gray scale difference among the plurality of thegray scale differences, and the minimum gray scale deference is smallerthan a first threshold, the judging unit is configured to determine thecurrent frame image part corresponding to the second gray scale as thefirst overlap region.

In one embodiment, the previous frame of fingerprint images includes theprevious frame image part, the current frame of fingerprint imagesincludes groups of a plurality of current frame image parts, and eachgroup of the plurality of current frame image parts includes a firstcurrent frame image part, a second current frame image part, and a thirdcurrent frame image part;

the judging unit is configured to calculate a first gray scaledifference between a first gray scale of the previous frame image partand a first gray scale of the first current frame image part of onegroup of current frame image parts, a second gray scale differencebetween the first gray scale of the previous frame image part and asecond gray scale of the second current frame image part of the onegroup of current frame image parts, and a third gray scale differencebetween the first gray scale of the previous frame image part and athird gray scale of the third current frame image part of the one groupof current frame image parts, respectively, to obtain a gray scale sumof the first gray scale difference, the second gray scale difference andthe third gray scale difference and, after a plurality of gray scalesums are obtained, to compare the plurality of gray scale sums;

when the gray scale sum of a group of current frame image parts has aminimum value among the plurality of the gray scale sums, the judgingunit compares the first gray scale difference, the second gray scaledifference, and the third gray scale difference corresponding to the onegroup of current frame image parts; and

when a value of a gray scale difference is minimum among the group andthe value is less than a second threshold, the judging unit determinesthe current frame image part corresponding to the gray scale differencehaving the minimum value as the first overlap region.

A method of fingerprint identification includes the steps of:

S1: collecting, by a fingerprint sensor, multiple frames of fingerprintimages sliding-inputted by a user

S2: judging, by a judging unit, whether, among the multiple frames offingerprint images, there is a first overlap region between a currentframe of fingerprint images and a previous frame of fingerprint images;when there is a first overlap region between a current frame offingerprint images and a previous frame of fingerprint images,proceeding to S3; and when there is not a first overlap region between acurrent frame of fingerprint images and a previous frame of fingerprintimages, returning to S1;

S3: removing, by the judging unit, the first overlap region from thecurrent frame of fingerprint images and superposing the previous frameof fingerprint images with the current frame of fingerprint imageswithout the first overlap region thereof to form a superposedfingerprint image; or removing, by the judging unit, the first overlapregion from the previous frame of fingerprint images and superposing thecurrent frame of fingerprint images with the previous frame offingerprint images without the first overlap region to form thesuperposed fingerprint image;

S4: judging, by the judging unit, whether there is a second overlapregion between a next frame of fingerprint images and the superposedfingerprint image, until completing judgment of all the multiple framesof fingerprint images to obtain a template fingerprint image;

S5: extracting and saving, by a processing unit, characteristic pointsof the complete template fingerprint image;

S6: collecting, by the fingerprint sensor, a to-be-identifiedfingerprint image pressing-inputted by the user;

S7: extracting, by the processing unit, characteristic points of theto-be-identified fingerprint image and determining whether thecharacteristic points of the to-be-identified fingerprint image matchwith the characteristic points of the template fingerprint image; whenthe characteristic points of the to-be-identified fingerprint imagematch with the characteristic points of the template fingerprint image,proceeding to S8; and when the characteristic points of theto-be-identified fingerprint image do not match with the characteristicpoints of the template fingerprint image, proceeding to S9;

S8: determining, by the processing unit, the to-be-identifiedfingerprint image as a matching fingerprint image; and

S9: determining, by the processing unit, the to-be-identifiedfingerprint image as a non-matching fingerprint image.

In one embodiment, Step S5 further comprises: performing, by, theprocessing unit filtering, binarization, and thinning processing on thetemplate fingerprint image to extract the characteristic points of thetemplate fingerprint image.

In one embodiment, the previous frame of fingerprint images includes theprevious frame image part, the current frame of fingerprint imagesincludes a plurality of current frame image parts, and Step S2 furthercomprises:

respectively calculating, by the judging unit, gray differences betweenthe first gray scale of the previous frame image part and correspondingsecond gray scales of the plurality of the current frame image parts toobtain a plurality of the gray scale differences, and comparing theplurality of the gray scale differences; and

when a gray scale difference between a second gray scale and the firstgray scale is a minimum gray scale difference among the plurality of thegray scale differences, and the minimum gray scale deference is smallerthan a first threshold, determining, by the judging unit, the currentframe image part corresponding to the second gray scale as the firstoverlap region.

In one embodiment, the previous frame of fingerprint images includes theprevious frame image part, the current frame of fingerprint imagesincludes groups of a plurality of current frame image parts, and eachgroup of the plurality of current frame image parts includes a firstcurrent frame image part, a second current frame image part, and a thirdcurrent frame image part; and Step S2 further comprises:

calculating, by the judging unit, a first gray scale difference betweena first gray scale of the previous frame image part and a first grayscale of the first current frame image part of one group of currentframe image parts, a second gray scale difference between the first grayscale of the previous frame image part and a second gray scale of thesecond current frame image part of the one group of current frame imageparts, and a third gray scale difference between the first gray scale ofthe previous frame image part and a third gray scale of the thirdcurrent frame image part of the one group of current frame image parts,respectively, to obtain a gray scale sum of the first gray scaledifference, the second gray scale difference and the third gray scaledifference and, after a plurality of gray scale sums are obtained,comparing the plurality of gray scale sums;

when the gray scale sum of a group of current frame image parts has aminimum value among the plurality of the gray scale sums, comparing, bythe judging unit, the first gray scale difference, the second gray scaledifference, and the third gray scale difference corresponding to the onegroup of current frame image parts; and

when a value of a gray scale difference is minimum among the group andthe value is less than a second threshold, determining, by the judgingunit, the current frame image part corresponding to the gray scaledifference having the minimum value as the first overlap region.

An electric equipment includes a fingerprint identification system, thefingerprint identification system includes a fingerprint sensor, ajudging unit and a processing unit, and

the fingerprint sensor collects multiple frames of fingerprint imagessliding-inputted by a user;

the judging unit determines whether, among the multiple frames offingerprint images, there is a first overlap region between a currentframe of fingerprint images and a previous frame of fingerprint images;

when there is a first overlap region between a current frame offingerprint images and a previous frame of fingerprint images, thejudging unit removes the first overlap region from the current frame offingerprint images and superposes the previous frame of fingerprintimages with the current frame of fingerprint images without the firstoverlap region thereof to form a superposed fingerprint image; or thejudging unit removes the first overlap region from the previous frame offingerprint images and superposes the current frame of fingerprintimages with the previous frame of fingerprint images without the firstoverlap region to form the superposed fingerprint image;

the judging unit also judges whether there is a second overlap regionbetween a next frame of fingerprint images and the superposedfingerprint image, until completing judgment of all the multiple framesof fingerprint images to obtain a template fingerprint image;

the processing unit extracts and saves characteristic points of thecomplete template fingerprint image;

when there is not a first overlap region between a current frame offingerprint images and a previous frame of fingerprint images, thefingerprint sensor collects new multiple frames of fingerprint imagessliding-inputted by the user;

the fingerprint sensor collects a to-be-identified fingerprint imagepressing-inputted by the user, and the processing unit extractscharacteristic points of the to-be-identified fingerprint image anddetermines whether the characteristic points of the to-be-identifiedfingerprint image match with the characteristic points of the templatefingerprint image;

when the characteristic points of the to-be-identified fingerprint imagematch with the characteristic points of the template fingerprint image,the processing unit determines the to-be-identified fingerprint image asa matching fingerprint image; and

when the characteristic points of the to-be-identified fingerprint imagedo not match with the characteristic points of the template fingerprintimage, the processing unit determines the to-be-identified fingerprintimage as a non-matching fingerprint image.

In one embodiment, the processing unit is configured to performfiltering, binarization, and thinning processing on the templatefingerprint image, and to extract the characteristic points of thetemplate fingerprint image.

In one embodiment, the previous frame of fingerprint images includes theprevious frame image part, the current frame of fingerprint imagesincludes a plurality of current frame image parts, and the judging unitrespectively calculate gray differences between the first gray scale ofthe previous frame image part and corresponding second gray scales ofthe plurality of the current frame image parts to obtain a plurality ofthe gray scale differences, and to compare the plurality of the grayscale differences; and

when a gray scale difference between a second gray scale and the firstgray scale is a minimum gray scale difference among the plurality of thegray scale differences, and the minimum gray scale deference is smallerthan a first threshold, the judging unit is configured to determine thecurrent frame image part corresponding to the second gray scale as thefirst overlap region.

In one embodiment, the previous frame of fingerprint images includes theprevious frame image part, the current frame of fingerprint imagesincludes groups of a plurality of current frame image parts, and eachgroup of the plurality of current frame image parts includes a firstcurrent frame image part, a second current frame image part, and a thirdcurrent frame image part;

the judging unit is configured to calculate a first gray scaledifference between a first gray scale of the previous frame image partand a first gray scale of the first current frame image part of onegroup of current frame image parts, a second gray scale differencebetween the first gray scale of the previous frame image part and asecond gray scale of the second current frame image to part of the onegroup of current frame image parts, and a third gray scale differencebetween the first gray scale of the previous frame image part and athird gray scale of the third current frame image part of the one groupof current frame image parts, respectively, to obtain a gray scale sumof the first gray scale difference, the second gray scale difference andthe third gray scale difference and, after a plurality of gray scalesums are obtained, to compare the plurality of gray scale sums;

when the gray scale sum of a group of current frame image parts has aminimum value among the plurality of the gray scale sums, the judgingunit compares the first gray scale difference, the second gray scaledifference, and the third gray scale difference corresponding to the onegroup of current frame image parts; and

when a value of a gray scale difference is minimum among the group andthe value is less than a second threshold, the judging unit determinesthe current frame image part corresponding to the gray scale differencehaving the minimum value as the first overlap region.

Additional aspect and advantages of the present disclosure will bepartly provided in the following description, and part of the additionalaspect and the advantages will become apparent from the followingdescription, or will be know from embodiments of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects and advantages of embodiments of the presentdisclosure will become apparent and more readily appreciated from thefollowing descriptions made with reference to the accompanying drawings,in which:

FIG. 1 is a block diagram of a fingerprint identification systemaccording to an embodiment of the present disclosure;

FIG. 2 is a diagram of a user inputting a fingerprint on a fingerprintsensor;

FIG. 3 is a diagram of a user inputting fingerprint atdifferent-positions of a finger on a fingerprint sensor;

FIG. 4 is a schematic diagram of a fingerprint identification systemaccording to an embodiment of the present disclosure;

FIG. 5 is another schematic diagram of a fingerprint identificationsystem according to an embodiment of the present disclosure;

FIG. 6 is a flow diagram of a fingerprint identification methodaccording to an embodiment of the present disclosure; and

FIG. 7 is a frame diagram of an electric equipment according to anembodiment of the present disclosure.

DETAILED DESCRIPTION

Embodiments of the present disclosure are described in detail below, andexamples of the embodiments are shown in accompanying drawings, whereinidentical or similar marks denote identical or similar components orcomponents with the same or similar function from beginning to end. Thefollowing embodiments described by referring to the accompanyingdrawings are illustrative, aim at explaining the present disclosure, andshould not be interpreted as limitations to the present disclosure.

In addition, the terms such as “first” and “second” are used merely forthe purpose of description, but shall not be construed as indicating orimplying relative importance or implicitly indicating a number of theindicated technical feature. Hence, the feature defined with “first” and“second” may explicitly or implicitly include at least one of thefeatures. In the description of the present disclosure, unless otherwiseexplicitly specifically defined, “multiple” means at least two, forexample, two or three.

In the present disclosure, unless otherwise explicitly specified ordefined, the terms such as “mount”, “connect”, “connection”, and “fix”should be interpreted in a broad sense. For example, a connection may bea fixed connection, or may be a detachable connection or an integralconnection; a connection may be a mechanical connection, or may be anelectrical connection; a connection may be a mechanical connection, ormay be an electrical connection, or may be used for intercommunication;a connection may be a direct connection, or may be an indirectconnection via an intermediate medium, or may be communication betweeninteriors of two elements or an interaction relationship between twoelements, unless otherwise explicitly defined. It may be appreciated bythose of ordinary skill in the art that the specific meanings of theaforementioned terms in the present disclosure can be understooddepending on specific situations.

Various embodiments and examples are provided in the followingdescription to implement different structures of the present disclosure.In order to simplify the present disclosure, certain elements andsettings will be described. However, these elements and settings areonly by way of example and are not intended to limit the presentdisclosure. In addition, reference numerals may be repeated in differentexamples in the present disclosure. This repeating is for the purpose ofsimplification and clarity and does not refer to relations betweendifferent embodiments and/or settings. Furthermore, examples ofdifferent processes and materials are provided in the presentdisclosure. However, it would be appreciated by those skilled in the artthat other processes and/or materials may be also applied.

Referring to FIG. 1, the fingerprint identification system 10 accordingto the present disclosure includes a fingerprint sensor 102, a judgingunit 104, and a processing unit 106.

The fingerprint sensor 102 is configured to collect multiple frames offingerprint images sliding-inputted by a user. The fingerprint sensor102, for example, could be a surface capacitive fingerprint sensor, witha size of about 4*8 mm, 508 dpi, a resolution of about 80*160. Themultiple frames of fingerprint images are inputted by the user in asliding-input format, referring to FIG. 2, where the user slides thefinger 100 through a detection panel of the fingerprint sensor 102 and,then, the fingerprint sensor 102 can collect multiple frames of slidingfingerprint images of the finger in a sequence.

The judging unit 104 is configured to judge whether, among the multipleframes of fingerprint images, there is a first overlap region between acurrent frame of fingerprint images and a previous frame of fingerprintimages. If yes, the judging unit 104 is also configured to remove thefirst overlap region from the current frame of fingerprint images and tosuperpose the previous frame of fingerprint images with the currentframe of fingerprint images without the first overlap region thereof toform a superposed fingerprint image. If no, the fingerprint sensor isconfigured to again collecting new multiple frames of fingerprint imagessliding-inputted by the user. The judging unit 104 is also configured tojudge whether there is a second overlap region between a next frame offingerprint images and the superposed fingerprint image, untilcompleting judgment of all the multiple frames of fingerprint images toobtain a template fingerprint image.

In certain other embodiments, the judging unit 104 can also beconfigured to remove the first overlap region from the previous frame offingerprint images and to superpose the current frame of fingerprintimages with the previous frame of fingerprint images without the firstoverlap region to form the superposed fingerprint image.

Because the area of the fingerprint sensor 102 is relatively small, andthe area of the fingerprint is relatively big, when collecting thefingerprint, the fingerprint sensor 102 can collect the multiplefingerprint images frame by frame and, when two adjacent frames offingerprint images have a part of same area, the judging unit 104 canstitch the two adjacent frames of fingerprint images as another frame offingerprint image. Therefore, referring to FIG. 3, the left side, themiddle, and the right side of the finger are respectivelysliding-inputted through the detection panel of the fingerprint sensor102 by the user. Each time the fingerprint is sliding-inputted, thejudging unit 104 stitches the multiple frames of fingerprint images,which are collected by the fingerprint sensor 102, as a templatefingerprint image frame, and three template fingerprint image frames canbe stitched together to form a complete template fingerprint image.

Specifically, in this embodiment, the previous frame of fingerprintimage includes a previous frame image part, the current frame offingerprint images includes groups of a plurality of current frame imageparts, and each group of the plurality of current frame image parts mayinclude a first current frame image part, a second current frame imagepart, and a third current frame image part.

The judging unit 104 is configured to calculate a first gray scaledifference between a first gray scale of the previous frame image partand a first gray scale of the first current frame image part of onegroup of current frame image parts, a second gray scale differencebetween the first gray scale of the previous frame image part and asecond gray scale of the second current frame image part of the onegroup of current frame image parts, and a third gray scale differencebetween the first gray scale of the previous frame image part and athird gray scale of the third current frame image part of the one groupof current frame image parts, respectively, to obtain a gray scale sumof the first gray scale difference, the second gray scale difference andthe third gray scale difference. After a plurality of gray scale sumsare obtained, the plurality of gray scale sums are compared.

When the gray scale sum of a group of current frame image parts has aminimum value among the plurality of the gray scale sums, the judgingunit 104 is configured to compare the first gray scale difference, thesecond gray scale difference, and the third gray scale differencecorresponding to the one group of current frame image parts.

When the value of a gray scale difference is minimum among the group,and the value is less than a threshold, the judging unit 104 isconfigured to determine the current frame image part corresponding tothe gray scale difference having the minimum value as the first overlapregion. If no gray scale difference having the minimum value less thanthe threshold, the judging unit 104 prompts the user to againsliding-input the fingerprint image.

For example, referring to FIG. 4, the previous frame of fingerprintimages I1 (the resolution is 8*128) includes the previous frame imagepart A1 (the resolution is 2*80), the current frame of fingerprintimages I2 (the resolution is 8*128) includes seven groups of currentframe image parts B1˜B7 (the resolution of each group of current frameimage parts Bn is 2*82, n=1, 2, . . . , 7).

The previous frame image part A1 is at a center location of last tworows of the previous frame of fingerprint images I1, that is, theprevious frame image part A1 is an image part from the 7^(th) row to the8^(th) row and from the 25^(th) column to the 104^(th) column of theprevious frame of fingerprint images I1.

Each group of current frame image parts Bn includes the first currentframe image part Bn1, the second current frame image part Bn2, and thethird current frame image part Bn3. The resolution of the first currentframe image part Bn1, the second current frame image part Bn2, and thethird current frame image part Bn3 is 2*80. The second current frameimage part Bn2 locates at middle of the group of current frame imagepart Bn, and at middle of the current frame of fingerprint images I2along a direction of resolution line. That is, the number of theresolution columns between the leftmost of the second current frameimage part Bn2 and the leftmost of the current frame of fingerprintimages I2 is equal to the number of the resolution columns between therightmost of the second current frame image part Bn2 and the rightmostof the current frame of fingerprint images I2. The first current frameimage part Bn1 shifts to left by one column from the second currentframe image part Bn2 along the direction of the resolution line, and thethird current frame image part Bn3 shifts to right by one column fromthe second current frame image part Bn2 along the direction of theresolution line. Thus, the shifted image parts are used to take accountin the factor that the user may turn the finger left and/or turn thefinger right in a process of sliding-inputting the fingerprint, suchthat an accuracy of fingerprint synthesis may be higher.

For example, for the group of current frame image parts B1, the group ofcurrent frame image parts B1 includes the first current frame image partB11, the second current frame image part B12, and the third currentframe image part B13. The first current frame image part B11 is theimage part from the 1^(st) row to the 2^(nd) row and from the 24^(th)column to the 103^(th) column of the current frame of fingerprint imagesI2, the second current frame image part B12 is the image part from the1^(st) row to the 2^(nd) row and from the 25^(th) column to the 104^(th)column of the current frame, and the third current frame image part B13is the image part from the 1^(st) row to the 2^(nd) row and from 26^(th)column to the 105^(th) column of the current frame.

For the group of current frame image parts B2, the group of currentframe image parts B2 includes the first current frame image part B21,the second current frame image part B22, and the third current frameimage part B23. The first current frame image part B21 is the image partfrom the 2^(nd) row to the 3^(rd) row and from the 24^(th) column to the103^(th) column of the current frame, the second current frame imagepart B22 is the image part from the 2^(nd) row to the 3^(rd) row andfrom the 25^(th) column to the 104^(th) column of the current frame, andthe third current frame image part B33 is the image part from the 2^(nd)row to the 3^(rd) row and from 26^(th) column to the 105^(th) column ofthe current frame. Other groups of current frame image parts can besimilarly formed.

The judging unit 104 is configured to calculate respectively gray scaledifferences between the first gray scale G1 of the previous frame imagepart A1 and the first gray scale Gn1 of the first current frame imagepart Bn1, the second gray scale Gn2 of the second current frame imagepart Bn2, and the third gray scale Gn3 of the third current frame imagepart Bn3 of a same current frame image part Bn, to obtain the first grayscale difference Dn1, the second gray scale difference Dn2 and the thirdgray scale difference Dn3; to calculate the gray scale sum of the firstgray scale difference Dn1, the second gray scale difference Dn2, and thethird gray scale difference Dn3 so as to obtain a plurality of the grayscale sums Sn, and to compare the plurality of the gray scale sums Sn.

When a gray scale sum Sn corresponding to one of the plurality of groupsof current frame image parts Bn is the minimum among the plurality ofgray scale sums, the judging unit 104 is configured to compare the firstgray scale difference Dn1, the second gray scale difference Dn2, and thethird gray scale difference Dn3 corresponding to the group of currentframe image parts Bn having the minimum gray scale sum.

When the minimum gray scale difference min_Dni, i=1, 2, 3, is obtained,and the minimum gray scale difference min_Dni is smaller than thethreshold, the judging unit 104 is configured to determine the currentframe image part Bni corresponding to the minimum gray scale differencemin_Dni as the first overlap region.

Specifically, the judging unit 104 is configured to respectivelycalculate the gray scale differences between the first gray scale G1 andthe first gray scale G11 of the first current frame image part B11, thesecond gray scale G12 of the second current frame image part B12, andthe third gray scale G13 of the third current frame image part B13 ofthe group of current frame image parts B1 to obtain the first gray scaledifference D11, the second gray scale difference D12 and the third grayscale difference D13, respectively, and to calculate the gray scale sumS1 of the first gray scale difference D11, the second gray scaledifference D12 and the third gray scale difference D13. Similarly, thejudging unit 104 calculates the gray scale sum S2 corresponding to thegroup of current frame image parts B2, the gray scale sum S3corresponding to the group of current frame image parts B3, the grayscale sum S4 corresponding to the group of current frame image parts B4,the gray scale sum S5 corresponding to the group of current frame imageparts B5, the gray scale sum S6 corresponding to the group of currentframe image parts B6 and the gray scale sum S7 corresponding to thegroup of current frame image parts B7.

The judging unit 104 compares the seven gray scale sums S1, S2, . . . ,S7. If the gray scale sum S1 corresponding to the group of current frameimage parts B1 is the minimum value among the seven gray scale sums, thejudging unit 104 further compares the first gray scale difference D11,the second gray scale difference D12, and the third gray scaledifference D13 corresponding to the group of current frame image partsB1.

If it is determined that the second gray scale difference D12 is theminimum gray scale difference and, as the minimum value, the second grayscale difference D12 is smaller than the threshold, the judging unit 104determines the current frame image part B12 corresponding to the minimumsecond gray scale difference D12 as the first overlap region.

The judging unit 104 removes the first overlap region B12 from thecurrent frame of fingerprint images I2, and then superposes the currentframe of fingerprint images I2 without the first overlap region B12 withthe previous frame of fingerprint images I1, such that the previousframe image part A1 of the previous frame of fingerprint images I1 islocated at the position where the first overlap region B12 was removedto obtain a superposed fingerprint image. The judging unit completes thedetermination of remaining multiple frames of fingerprint images andobtains a complete template fingerprint image.

The processing unit 106 is configured to extract and save thecharacteristic points of the complete template fingerprint image. Theprocessing unit 106 performs filtering, binarization, and thinningprocessing on the template fingerprint image to collect characteristicpoint information. The processing unit 106 establishes a fingerprinttemplate database, and the template fingerprint image in the databaseare used in subsequent matching processes.

In a subsequent matching process, the fingerprint sensor 102 is alsoconfigured to collect a to-be-identified fingerprint imagepressing-inputted by a user. The processing unit 106 is configured tojudge whether the characteristic points of the to-be-identifiedfingerprint image matches with the characteristic points of the templatefingerprint image. If yes, the processing unit 106 is configured todetermine the to-be-identified fingerprint image as the matchingfingerprint image; and if no, the processing unit 106 is configured todetermine the to-be-identified fingerprint image as the non-matchingfingerprint image. When the collected characteristic point of theto-be-identified fingerprint image matches with the characteristicpoints of the template fingerprint image, the matching operation issuccessful.

The fingerprint identification system 10, when establishing a templatefingerprint database, uses the fingerprint sensor 102 to collect themultiple frames of fingerprint images sliding-inputted by the user, anduses the judging unit 104 to superpose the sliding-inputted framestogether using an image-stitching technique. Thus, the amount ofinformation collected by the fingerprint sensor for each sliding-inputis much more than the amount of information collected by the fingerprintsensor for each pressing-input under existing methods, and the inputefficiency is much higher than that of existing methods. The inputtingprocess can be completed by one-time collection of the left side, middleside, and right side of the finger, respectively, and is convenient toinput, avoiding complex operations and improving user experience. It canbe understood that, through a user interface such as a user interfacedisplayed on a display screen, the fingerprint identification system 10prompts the user for sliding-inputting fingerprint at a correspondingposition of the finger 100, for example, fingerprint at the left side ofthe finger 100. After the fingerprint at the left side of the finger 100is inputted successfully, the user continues to completefingerprint-inputting of fingerprint at the right side and the middleside of the finger 100 under the prompt of the fingerprintidentification system 10.

In the subsequent matching process, the user does not need tosliding-input the fingerprint and there is no image-stitching needed,but only needs to press on the detecting panel of the fingerprint sensor102 to collect the fingerprint. That is, in the subsequent matchingprocess, the user presses the finger on the fingerprint sensor 102, andthe fingerprint sensor 102 can collect the fingerprint of thepressed-part of the finger, and the processing unit 106 can compare thecollected fingerprint with template fingerprint database. It is possiblethat the user uses regular angles when inputting the fingerprints, butthe matching process can still be successful at various angles.

Another embodiment of the present disclosure provides a fingerprintidentification system. The fingerprint identification system is largelythe same as the fingerprint identification system provided in theprevious embodiment but with a few differences. In the presentembodiment, the previous frame of fingerprint images includes a previousframe image part, the current frame of fingerprint images includes aplurality of the current frame image parts, and the judging unit isconfigured to respectively calculate the gray difference between thefirst gray scale of the previous frame image part and correspondingsecond gray scales of the plurality of the current frame image parts toobtain the plurality of the gray scale differences, and to compare theplurality of the gray scale differences.

When a gray scale difference between a second gray scale and the firstgray scale is a minimum gray scale difference among the plurality of thegray scale differences, and the minimum gray scale deference is smallerthan a threshold, the judging unit is configured to determine thecurrent frame image part corresponding to the second gray scale as thefirst overlap region. If there is no minimum gray scale differencesmaller than the threshold, the judging unit 104 prompts the user toagain sliding-input frames of fingerprint images.

For example, referring to FIG. 5, the previous frame of fingerprintimages 01 (the resolution is 8*128) includes the previous frame imagepart P1 (the resolution is 2*80), the current frame of fingerprintimages 02 (the resolution is 8*128) includes seven current frame imageparts Qn (n=1, 2, . . . , 7).

The previous frame image part P1 is at a location of last two lines ofthe previous frame of fingerprint images 01, that is, the previous frameimage part P1 is the image part of twenty-fifth to 104^(th) columns ofseventh to eighth lines of the previous frame of fingerprint images 01.

The current frame image parts Qn are located at the middle of thecurrent frame of fingerprint images 02 and along a direction of theresolution row, that is, the number of the resolution columns betweenthe leftmost of a current frame image part Qn and the leftmost of thecurrent frame of fingerprint images 02 is equal to the number of theresolution columns between the rightmost of the current frame image partQn and the rightmost of the current frame of fingerprint images 02.

For example, for the current frame image part Q1, the current frameimage part Q1 is the image part from the 1^(st) row to the 2^(nd) rowand from the 25^(th) column to the 104^(th) column of the current frameof fingerprint images 02.

For the current frame image part Q2, the current frame image part Q2 isthe image part from the 2^(nd) row to the 3^(rd) row and from the25^(th) column to the 104^(th) column of the current frame offingerprint images 02. Other current frame image parts may be similarlyobtained.

The judging unit 104 is configured to respectively calculate the grayscale difference between the first gray scale G0 of the previous frameimage part P1 and seven second gray scales Gn of the seven current frameimage parts Qn to obtain seven gray scale differences Dn, and to comparethe seven gray scale differences Dn.

If a gray scale difference Dn between a second gray scale Gn and thefirst gray scale G0 is the minimum value min_Dn among the plurality ofthe gray scale differences, and the minimum value min_Dn is smaller thanthe threshold, the judging unit is configured to determine the currentframe image part Qn corresponding to the second gray scale Gn having theminimum value min_Dn as the first overlap region.

For example, if the gray scale difference D2 between the second grayscale G2 and the first gray scale G0 is the minimum value among theseven gray scale differences, and the gray scale difference D2 issmaller than the threshold, the judging unit is configured to determinethe current frame image part Q2 corresponding to the second gray scaleG2 as the first overlap region.

The judging unit removes the first overlap region Q2 from the currentframe of fingerprint images 02, and then superposes the current frame offingerprint images 02 without the first overlap region Q2 with theprevious frame of fingerprint images 01, such that the previous frameimage part P1 of the previous frame of fingerprint images 01 is locatedat the position where the first overlap region Q2 was removed to obtaina superposed fingerprint image. The judging unit completes thedetermination of remaining multiple frames of fingerprint images andobtains a complete template fingerprint image.

The fingerprint identification system according to this embodimentrequires the user not to rotate the finger when sliding-inputting thefingerprint, so as to improve the inputting success rate.

Referring to FIG. 6, a fingerprint identification method according to anembodiment of the present disclosure is provided, the method includesthe followings:

S1: the fingerprint sensor collects multiple frames of fingerprintimages sliding-inputted by a user.

S2: the judging unit determines whether, among the multiple frames offingerprint images, there is a first overlap region between a currentframe of fingerprint images and a previous frame of fingerprint images.If yes, the method proceeds to Step S3; if no, the method returns toStep S1.

S3: the judging unit removes the first overlap region from the currentframe of fingerprint images and superposes the previous frame offingerprint images with the current frame of fingerprint images withoutthe first overlap region thereof to form a superposed fingerprint image;or the judging unit removes the first overlap region from the previousframe of fingerprint images and superposes the current frame offingerprint images with the previous frame of fingerprint images withoutthe first overlap region to form the superposed fingerprint image.

S4: the judging unit judges whether there is a second overlap regionbetween a next frame of fingerprint images and the superposedfingerprint image, until completing judgment of all the multiple framesof fingerprint images to obtain a template fingerprint image.

S5: the processing unit extracts and saves the characteristic points ofthe complete template fingerprint image.

S6: the fingerprint sensor collects a to-be-identified fingerprint imagepressing-inputted by the user.

S7: the processing unit extracts characteristic points of theto-be-identified fingerprint image, and determines whether thecharacteristic points of the to-be-identified fingerprint image matchwith the characteristic points of the template fingerprint image. Ifyes, the method proceeds to Step S8; if no, the method proceeds to StepS9.

S8: the processing unit determines the to-be-identified fingerprintimage as the matching fingerprint image.

S9: the processing unit determines the to-be-identified fingerprintimage as the non-matching fingerprint image.

It is understood that the above fingerprint identification method can beimplemented by the fingerprint identification system. The Steps S3 andS4 can be understood as stitching steps of the fingerprint image.

In one embodiment, in Step S5, the processing unit performs filtering,binarization, and thinning processing on the template fingerprint image,and extracts the characteristic points of the template fingerprintimage.

In one embodiment, in Step S2, the previous frame of fingerprint imagesincludes the previous frame image part, the current frame of fingerprintimages includes a plurality of current frame image parts, and thejudging unit respectively calculates the gray difference between thefirst gray scale of the previous frame image part and correspondingsecond gray scales of the plurality of the current frame image parts toobtain the plurality of the gray scale differences, and compares theplurality of the gray scale differences.

When a gray scale difference between a second gray scale and the firstgray scale is a minimum gray scale difference among the plurality of thegray scale differences, and the minimum gray scale deference is smallerthan a threshold, the judging unit is configured to determine thecurrent frame image part corresponding to the second gray scale as thefirst overlap region.

In one embodiment, in Step S2, the previous frame of fingerprint imagesincludes the previous frame image part, the current frame of fingerprintimages includes groups of a plurality of current frame image parts, andeach group of the plurality of current frame image parts may include afirst current frame image part, a second current frame image part, and athird current frame image part.

The judging unit respectively calculates a first gray scale differencebetween a first gray scale of the previous frame image part and a firstgray scale of the first current frame image part of one group of currentframe image parts, a second gray scale difference between the first grayscale of the previous frame image part and a second gray scale of thesecond current frame image part the one group of current frame imageparts, and a third gray scale difference between the first gray scale ofthe previous frame image part and a third gray scale of the thirdcurrent frame image part the one group of current frame image parts,respectively, to obtain a gray scale sum of the first gray scaledifference, the second gray scale difference and the third gray scaledifference and, after a plurality of gray scale sums are obtained,compares the plurality of gray scale sums.

When the gray scale sum of a group of current frame image parts has aminimum value among the plurality of the gray scale sums, the judgingunit compares the first gray scale difference, the second gray scaledifference, and the third gray scale difference corresponding to the onegroup of current frame image parts.

When the value of a gray scale difference is minimum among the group,and the value is less than a threshold, the judging unit determines thecurrent frame image part corresponding to the gray scale differencehaving the minimum value as the first overlap region.

According to the above fingerprint identification method, whenestablishing the template fingerprint database, the fingerprint sensoris used to collect the multiple frames of fingerprint imagessliding-inputted by the user, and the judging unit 104 superposes thesliding-inputted frames together using an image-stitching technique.Thus, the amount of information collected by the fingerprint sensor foreach sliding-input is much more than the amount of information collectedby the fingerprint sensor for each pressing-input under existingmethods, and the input efficiency is much higher than that of existingmethods. The inputting process can be completed by one-time collectionof the left side, middle side, and right side of the finger,respectively, and is convenient to input, avoiding complex operationsand improving user experience. In the subsequent matching process, theuser presses the finger on the fingerprint sensor, and the fingerprintsensor can collect the fingerprint of the pressed-part of the finger,and the processing unit can compare the collected fingerprint withtemplate fingerprint database. It is possible that the user uses regularangles when inputting the fingerprints, but the matching process canstill be successful at various angles.

Referring to FIG. 7, the electric equipment 20 according to embodimentsof the present disclosure includes the fingerprint identification systemaccording to any embodiment of the present disclosure. The electricequipment 20 can be a mobile phone, a tablet computer and other terminalequipment. When the fingerprint identification system is used for amobile phone, as shown in the FIG. 2, the fingerprint sensor 202 islocated on a lower Home key of an electric equipment 20, on a lateralside of the mobile phone, or on a back side of the mobile phone, etc.When the user uses the electric equipment for the first time, referringto FIG. 3, the user presses the finger on the fingerprint sensor, andrespectively slides the right side of the finger, the middle side of thefinger, and the right side of the finger through the fingerprint sensor202. Thus, the characteristic points of a whole finger 100 can berecorded via sliding-inputting the fingerprint. When the usersubsequently uses the electric equipment to unlock the electricequipment, the user only needs to press the finger 100 on thefingerprint sensor 202, without the need to slide the finger, thefingerprint can be successfully recognized from all angles.

Reference throughout this specification to “an embodiment,” “someembodiments,” “one embodiment”, “another example,” “an example,” “aspecific example,” or “some examples,” means that a particular feature,structure, material, or characteristic described in connection with theembodiment or example is included in at least one embodiment or exampleof the present disclosure. Thus, the appearances of the phrases such as“in some embodiments,” “in one embodiment”, “in an embodiment”, “inanother example,” “in an example,” “in a specific example,” or “in someexamples,” in various places throughout this specification are notnecessarily referring to the same embodiment or example of the presentdisclosure. Furthermore, the particular features, structures, materials,or characteristics may be combined in any suitable manner in one or moreembodiments or examples.

In addition, the terms such as “first” and “second” are used merely forthe purpose of description, but shall not be construed as indicating orimplying relative importance or implicitly indicating a number of theindicated technical feature. Hence, the feature defined with “first” and“second” may explicitly or implicitly include at least one of thefeatures. In the description of the present disclosure, unless otherwiseexplicitly specifically defined, “multiple” means at least two, forexample, two or three.

Any procedure or method described in the flow charts or described in anyother way herein may be understood to comprise one or more modules,portions or parts for storing executable codes that realize particularlogic functions or procedures. Moreover, advantageous embodiments of thepresent disclosure comprise other implementations in which the order ofexecution is different from that which is depicted or discussed,including executing functions in a substantially simultaneous manner orin an opposite order according to the related functions. This should beunderstood by those skilled in the art which embodiments of the presentdisclosure belong to.

The logic and/or step described in other manners herein or shown in theflow chart, for example, a particular sequence table of executableinstructions for realizing the logical function, may be specificallyachieved in any computer readable medium to be used by the instructionexecution system, device or equipment (such as the system based oncomputers, the system comprising processors or other systems capable ofobtaining the instruction from the instruction execution system, deviceand equipment and executing the instruction), or to be used in groupwith the instruction execution system, device and equipment.

It is understood that each part of the present disclosure may berealized by the hardware, software, firmware or their group. In theabove embodiments, a plurality of steps or methods may be realized bythe software or firmware stored in the memory and executed by theappropriate instruction execution system. For example, if it is realizedby the hardware, likewise in another embodiment, the steps or methodsmay be realized by one or a group of the following techniques known inthe art: a discrete logic circuit having a logic gate circuit forrealizing a logic function of a data signal, an application-specificintegrated circuit having an appropriate group logic gate circuit, aprogrammable gate array (PGA), a field programmable gate array (FPGA),etc.

Those skilled in the art shall understand that all or parts of the stepsin the above exemplifying method of the present disclosure may beachieved by commanding the related hardware with programs. The programsmay be stored in a computer readable storage medium, and the programscomprise one or a group of the steps in the method embodiments of thepresent disclosure when run on a computer.

In addition, each function cell of the embodiments of the presentdisclosure may be integrated in a processing module, or these cells maybe separate physical existence, or two or more cells are integrated in aprocessing module. The integrated module may be realized in a form ofhardware or in a form of software function modules. When the integratedmodule is realized in a form of software function module and is sold orused as a standalone product, the integrated module may be stored in acomputer readable storage medium.

Although explanatory embodiments have been shown and described, it wouldbe to appreciated by those skilled in the art that the above embodimentscannot be construed to limit the present disclosure, and changes,alternatives, and modifications can be made in the embodiments withoutdeparting from spirit, principles and scope of the present disclosure.

1. A fingerprint identification system, comprising a fingerprint sensor,a judging unit, and a processing unit, wherein: the fingerprint sensorcollects multiple frames of fingerprint images sliding-inputted by auser; the judging unit determines whether, among the multiple frames offingerprint images, there is a first overlap region between a currentframe of fingerprint images and a previous frame of fingerprint images;when there is a first overlap region between the current frame offingerprint images and the previous frame of fingerprint images, thejudging unit removes the first overlap region from the current frame offingerprint images and superposes the previous frame of fingerprintimages with the current frame of fingerprint images without the firstoverlap region thereof to form a superposed fingerprint image; or thejudging unit removes the first overlap region from the previous frame offingerprint images and superposes the current frame of fingerprintimages with the previous frame of fingerprint images without the firstoverlap region to form the superposed fingerprint image; the judgingunit also judges whether there is a second overlap region between a nextframe of fingerprint images and the superposed fingerprint image, untilcompleting judgment of all the multiple frames of fingerprint images toobtain a template fingerprint image; when there is not a first overlapregion between the current frame of fingerprint images and the previousframe of fingerprint images, the fingerprint sensor collects newmultiple frames of fingerprint images sliding-inputted by the user; theprocessing unit extracts and saves characteristic points of the templatefingerprint image; the fingerprint sensor collects a to-be-identifiedfingerprint image pressing-inputted by the user, and the processing unitextracts characteristic points of the to-be-identified fingerprint imageand determines whether the characteristic points of the to-be-identifiedfingerprint image match with the characteristic points of the templatefingerprint image; when the characteristic points of theto-be-identified fingerprint image match with the characteristic pointsof the template fingerprint image, the processing unit determines theto-be-identified fingerprint image as a matching fingerprint image; andwhen the characteristic points of the to-be-identified fingerprint imagedo not match with the characteristic points of the template fingerprintimage, the processing unit determines the to-be-identified fingerprintimage as a non-matching fingerprint image.
 2. The fingerprintidentification system according to claim 1, wherein the processing unitis configured to perform filtering, binarization, and thinningprocessing on the template fingerprint image, and to extract thecharacteristic points of the template fingerprint image.
 3. Thefingerprint identification system according to claim 1, wherein: theprevious frame of fingerprint images includes a previous frame imagepart, the current frame of fingerprint images includes a plurality ofcurrent frame image parts, and the judging unit respectively calculatesgray differences between a first gray scale of the previous frame imagepart and corresponding second gray scales of the plurality of thecurrent frame image parts to obtain a plurality of the gray scaledifferences, and compares the plurality of the gray scale differences;and when a gray scale difference between a second gray scale and thefirst gray scale is a minimum gray scale difference among the pluralityof the gray scale differences, and the minimum gray scale deference issmaller than a first threshold, the judging unit is configured todetermine the current frame image part corresponding to the second grayscale as the first overlap region.
 4. The fingerprint identificationsystem according to claim 1, wherein: the previous frame of fingerprintimages includes the previous frame image part, the current frame offingerprint images includes groups of a plurality of current frame imageparts, and each group of the plurality of current frame image partsincludes a first current frame image part, a second current frame imagepart, and a third current frame image part; the judging unit isconfigured to calculate a first gray scale difference between a firstgray scale of the previous frame image part and a first gray scale ofthe first current frame image part of one group of current frame imageparts, a second gray scale difference between the first gray scale ofthe previous frame image part and a second gray scale of the secondcurrent frame image part the one group of current frame image parts, anda third gray scale difference between the first gray scale of theprevious frame image part and a third gray scale of the third currentframe image part the one group of current frame image parts,respectively, to obtain a gray scale sum of the first gray scaledifference, the second gray scale difference and the third gray scaledifference and, after a plurality of gray scale sums are obtained, tocompare the plurality of gray scale sums; when the gray scale sum of agroup of current frame image parts has a minimum value among theplurality of the gray scale sums, the judging unit compares the firstgray scale difference, the second gray scale difference, and the thirdgray scale difference corresponding to the one group of current frameimage parts; and when a value of a gray scale difference is minimumamong the group and the value is less than a second threshold, thejudging unit determines the current frame image part corresponding tothe gray scale difference having the minimum value as the first overlapregion.
 5. A method of fingerprint identification, comprising: S1:collecting, by a fingerprint sensor, multiple frames of fingerprintimages sliding-inputted by a user S2: judging, by a judging unit,whether, among the multiple frames of fingerprint images, there is afirst overlap region between a current frame of fingerprint images and aprevious frame of fingerprint images; when there is a first overlapregion between the current frame of fingerprint images and the previousframe of fingerprint images, proceeding to S3; and when there is not afirst overlap region between the current frame of fingerprint images andthe previous frame of fingerprint images, returning to S1; S3: removing,by the judging unit, the first overlap region from the current frame offingerprint images and superposing the previous frame of fingerprintimages with the current frame of fingerprint images without the firstoverlap region thereof to form a superposed fingerprint image; orremoving, by the judging unit, the first overlap region from theprevious frame of fingerprint images and superposing the current frameof fingerprint images with the previous frame of fingerprint imageswithout the first overlap region to form the superposed fingerprintimage; S4: judging, by the judging unit, whether there is a secondoverlap region between a next frame of fingerprint images and thesuperposed fingerprint image, until completing judgment of all themultiple frames of fingerprint images to obtain a template fingerprintimage; S5: extracting and saving, by a processing unit, characteristicpoints of the template fingerprint image; S6: collecting, by thefingerprint sensor, a to-be-identified fingerprint imagepressing-inputted by the user; S7: extracting, by the processing unit,characteristic points of the to-be-identified fingerprint image anddetermining whether the characteristic points of the to-be-identifiedfingerprint image match with the characteristic points of the templatefingerprint image; when the characteristic points of theto-be-identified fingerprint image match with the characteristic pointsof the template fingerprint image, proceeding to S8; and when thecharacteristic points of the to-be-identified fingerprint image do notmatch with the characteristic points of the template fingerprint image,proceeding to S9; S8: determining, by the processing unit, theto-be-identified fingerprint image as a matching fingerprint image; andS9: determining, by the processing unit, the to-be-identifiedfingerprint image as a non-matching fingerprint image.
 6. The method offingerprint identification according to claim 5, wherein Step S5 furthercomprises: performing, by the processing unit filtering, binarization,and thinning processing on the template fingerprint image to extract thecharacteristic points of the template fingerprint image.
 7. The methodof fingerprint identification according to claim 5, wherein: theprevious frame of fingerprint images includes the previous frame imagepart, the current frame of fingerprint images includes a plurality ofcurrent frame image parts, and Step S2 further comprises: respectivelycalculating, by the judging unit, gray differences between the firstgray scale of the previous frame image part and corresponding secondgray scales of the plurality of the current frame image parts to obtaina plurality of the gray scale differences, and comparing the pluralityof the gray scale differences; and when a gray scale difference betweena second gray scale and the first gray scale is a minimum gray scaledifference among the plurality of the gray scale differences, and theminimum gray scale deference is smaller than a first threshold,determining, by the judging unit, the current frame image partcorresponding to the second gray scale as the first overlap region. 8.The method of fingerprint identification according to claim 5, wherein:the previous frame of fingerprint images includes the previous frameimage part, the current frame of fingerprint images includes groups of aplurality of current frame image parts, and each group of the pluralityof current frame image parts includes a first current frame image part,a second current frame image part, and a third current frame image part;and Step S2 further comprises: calculating, by the judging unit, a firstgray scale difference between a first gray scale of the previous frameimage part and a first gray scale of the first current frame image partof one group of current frame image parts, a second gray scaledifference between the first gray scale of the previous frame image partand a second gray scale of the second current frame image part the onegroup of current frame image parts, and a third gray scale differencebetween the first gray scale of the previous frame image part and athird gray scale of the third current frame image part the one group ofcurrent frame image parts, respectively, to obtain a gray scale sum ofthe first gray scale difference, the second gray scale difference andthe third gray scale difference and, after a plurality of gray scalesums are obtained, comparing the plurality of gray scale sums; when thegray scale sum of a group of current frame image parts has a minimumvalue among the plurality of the gray scale sums, comparing, by thejudging unit, the first gray scale difference, the second gray scaledifference, and the third gray scale difference corresponding to the onegroup of current frame image parts; and when a value of a gray scaledifference is minimum among the group and the value is less than asecond threshold, determining, by the judging unit, the current frameimage part corresponding to the gray scale difference having the minimumvalue as the first overlap region.
 9. An electric equipment, comprising:a fingerprint identification system, comprising a fingerprint sensor, ajudging unit, and a processing unit, wherein: the fingerprint sensorcollects multiple frames of fingerprint images sliding-inputted by auser; the judging unit determines whether, among the multiple frames offingerprint images, there is a first overlap region between a currentframe of fingerprint images and a previous frame of fingerprint images;when there is a first overlap region between the current frame offingerprint images and the previous frame of fingerprint images, thejudging unit removes the first overlap region from the current frame offingerprint images and superposes the previous frame of fingerprintimages with the current frame of fingerprint images without the firstoverlap region thereof to form a superposed fingerprint image; or thejudging unit removes the first overlap region from the previous frame offingerprint images and superposes the current frame of fingerprintimages with the previous frame of fingerprint images without the firstoverlap region to form the superposed fingerprint image; the judgingunit also judges whether there is a second overlap region between a nextframe of fingerprint images and the superposed fingerprint image, untilcompleting judgment of all the multiple frames of fingerprint images toobtain a template fingerprint image; the processing unit extracts andsaves characteristic points of the template fingerprint image; whenthere is not a first overlap region between the current frame offingerprint images and the previous frame of fingerprint images, thefingerprint sensor collects new multiple frames of fingerprint imagessliding-inputted by the user; the fingerprint sensor collects ato-be-identified fingerprint image pressing-inputted by the user, andthe processing unit extracts characteristic points of theto-be-identified fingerprint image and determines whether thecharacteristic points of the to-be-identified fingerprint image matchwith the characteristic points of the template fingerprint image; whenthe characteristic points of the to-be-identified fingerprint imagematch with the characteristic points of the template fingerprint image,the processing unit determines the to-be-identified fingerprint image asa matching fingerprint image; and when the characteristic points of theto-be-identified fingerprint image do not match with the characteristicpoints of the template fingerprint image, the processing unit determinesthe to-be-identified fingerprint image as a non-matching fingerprintimage.
 10. The electric equipment according to claim 9, wherein theprocessing unit is configured to perform filtering, binarization, andthinning processing on the template fingerprint image, and to extractthe characteristic points of the template fingerprint image.
 11. Theelectric equipment according to claim 9, wherein the previous frame offingerprint images includes the previous frame image part, the currentframe of fingerprint images includes a plurality of current frame imageparts, and the judging unit respectively calculates gray differencesbetween the first gray scale of the previous frame image part andcorresponding second gray scales of the plurality of the current frameimage parts to obtain a plurality of the gray scale differences, andcompares the plurality of the gray scale differences; and when a grayscale difference between a second gray scale and the first gray scale isa minimum gray scale difference among the plurality of the gray scaledifferences, and the minimum gray scale deference is smaller than afirst threshold, the judging unit is configured to determine the currentframe image part corresponding to the second gray scale as the firstoverlap region.
 12. The electric equipment according to claim 9, whereinthe previous frame of fingerprint images includes the previous frameimage part, the current frame of fingerprint images includes groups of aplurality of current frame image parts, and each group of the pluralityof current frame image parts includes a first current frame image part,a second current frame image part, and a third current frame image part;the judging unit is configured to calculate a first gray scaledifference between a first gray scale of the previous frame image partand a first gray scale of the first current frame image part of onegroup of current frame image parts, a second gray scale differencebetween the first gray scale of the previous frame image part and asecond gray scale of the second current frame image part one group ofcurrent frame image parts, and a third gray scale difference between thefirst gray scale of the previous frame image part and a third gray scaleof the third current frame image part, respectively, to obtain a grayscale sum of the first gray scale difference, the second gray scaledifference and the third gray scale difference and, after a plurality ofgray scale sums are obtained, to compare the plurality of gray scalesums; when the gray scale sum of a group of current frame image partshas a minimum value among the plurality of the gray scale sums, thejudging unit compares the first gray scale difference, the second grayscale difference, and the third gray scale difference corresponding tothe group of current frame image parts; and when a value of a gray scaledifference is minimum among the group and the value is less than asecond threshold, the judging unit determines the current frame imagepart corresponding to the gray scale difference having the minimum valueas the first overlap region.